The aim of this work is to present a fast and in situ diffusion modeling technique to extract essential electrochemical parameters from liquid-phase diffusion which can be used to implement a realistic battery in a pseudo-2D finite element modeling environment. A generalized Warburg element was used within an extended Randles equivalent circuit to obtain an appropriate fit on non-ideal diffusion impedance. Based on the calculation method presented in this paper, the values of diffusion-related parameters such as the cross-sectional area of the separator Asep, cell thickness Lcell as well as liquid-phase and solid-phase diffusion coefficients Dl and Ds were derived, successfully. A characteristic cell which allowed the exchange current density i0 and reaction rate constant k0 to be calculated was also established. The experimental data was measured by electrochemical impedance spectroscopy (EIS), resistivity measurement and the galvanostatic intermittent titration technique (GITT). The results show that our hypothesis to extract essential electrochemical parameters from the tail part of diffusion impedance is correct. The applicability of our concept is confirmed by the prosperous validation results produced by computed tomography (CT) and battery dynamics simulation in finite-element environment. Due to the inherent limitations of the pseudo-2D Doyle-Fuller-Newman (DFN) model, our technique is accordingly valid within the current range of 0–1 C.
<p class="Abstract"><span lang="EN-US">In this work the input and output capacitors of a digitally controlled Buck converter have been tested in 4 different cases with unused and worn out capacitors. The information extracted from interactions between the subsystems of an electric energy conversion system requires the implementation of the whole system from network to load. A complex simulation environment has been implemented where digital and analogue domains can be connected. The input and output capacitor aging have a significant influence on time domain characteristics, but the evaluation of frequency-domain data is supposed to be required to extract information from the noisy and distorted time-domain signal. The presented diagnostic approach aims to analyze signals that are used by the control loop in order to avoid expensive additions to existing circuits.</span></p>
The aim of this paper is to present an application of the generalized Warburg element and Constant Phase Element (CPE) for non-Fickian diffusion modeling. These distributed elements are intended to provide a better fit of low-frequency impedance data than the standard finite-length Warburg element in the case of most batteries. In addition, the current study demonstrates the ambiguity of the finite-length Warburg element if impedance data is insufficient within the verylow-frequency impedance spectrum. In order to select the appropriate Randles circuit for non-Fickian diffusion modeling, several configurations have been investigated. Based on the best fit of impedance data, the State-of-Charge (SoC) dependency of the Randles circuit parameters has also been analyzed. This study concerns a Samsung ICR18650-26F 2600 mAh battery cell which was subjected to Electrochemical Impedance Spectroscopy (EIS) measurements between 10 mHz and 100 kHz as a function of SoC. The results were plotted and compared in the form of Nyquist plots. The Randles circuit parameters such as the resistances Rs and Rct, double-layer C dl , leaky capacitance CPE and Warburg coefficients were estimated using ZView software. The present paper shows that CPE -and its QPE form -is a recommended choice to yield the best fit in terms of non-Fickian diffusion impedance. In addition, using CPE is a better alternative to avoid problems with initial values and multiple local solutions, which may exist in the case of the Warburg element. The resultant Randles circuit parameters and their SoC characteristics can be effectively used in further electrochemical modeling.
The paper presents a current impulse-based excitation method for lead-acid batteries in order to define the initial electrical parameters for model-based online estimators. The presented technique has the capability to track the SoC (State of Charge) of a battery, however, it is not intended to be used for online SoC estimations. The method is based on the battery’s electrical equivalent Randles’ model [1]. Load current impulse excitation was applied to the battery clamps during discharge while the voltage and current was logged. Based on the Randles’ model, a model function and a fit function were implemented and used by exponential regression based on the measured data. The diffusion-related non-linear characteristic of the battery was approximated by a capacitorlike linear voltage function for speed and simplicity. The initial capacitance of this bulk capacitor was estimated by linear regression on measurements recorded in the laboratory. Then, the RC parameters of the equivalent battery model were derived from exponential regression on transients during each current impulse cycle. The battery model with initial RC parameters is suitable for model-based online observers.
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